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Build better models with extensive capabilities and calculations

Use intuitive reports that display a complete picture of possible outcomes and calculations


Produce powerful valuations for project finance, tax assessments, budgeting, rate cases, and developing hedging strategies.


EnCompass provides a detailed commitment and dispatch optimization model to capture all operating constraints. This allows you to project future operations and financial metrics for a single power project or a portfolio of energy assets. Utilize better reporting and tools to forecast expected future market conditions, and assess the risk associated with uncertain and volatile market drivers.

EnCompass Interval Report showing dispatch stack with prices, generation, and ancillary services


Advanced risk modeling can be applied to any time series value, commodity price, interest rate, cost, demand, and renewable generation.


Utilize a two-factor mean-reverting model with short-term market volatility that tends toward a long-term fundamental outlook, which can be uncertain. Probability distributions can be lognormal, suitable for prices that are positive and skewed higher, as well as normal or uniform. Historical distributions that draw from actual past conditions inform weather-related variables such as demand and renewable generation. Correlation can also be defined among time series to represent the inter-dependence on market drivers.

EnCompass Interval Resource Report showing prices, generation, and ancillary services



EnCompass uses Monte Carlo sampling to assess market and portfolio impacts due to uncertain prices and volume. This sampling can be completely random, or utilize Latin Hypercube Sampling, which takes points equally across a distribution and requires fewer draws for convergence. The Position report displays a complete picture of all possible outcomes and calculates and displays relevant statistics including mean, deviation, confidence intervals, and correlation factors. Scatter plots and box-and-whiskers charts provide a visual indication of relationships and distributions. Financial contracts such as fuel cost hedges may be added after simulations to assess the impacts on expected values and volatility.

Monte Carlo settings


Perform a full optimization of all resources, subject to a complete set of operating costs and constraints.

By utilizing Mixed Integer Programming, EnCompass determines the best combination of resources to commit and the appropriate dispatch levels for each operating day’s intervals. In addition to minimum uptime and downtime requirements, EnCompass can cap the number of starts and shutdowns, and recognize costs and fuel requirements for hot, warm, and cold starts and shutdowns.

Heat rates and dispatch costs are set for the minimum (no-load) operating level, as well as any number of blocks up to maximum capacity. You can define any number of fuels may be defined for a resource, and EnCompass will utilize the least-cost fuel, subject to minimum and maximum limits.

Dependency constraints and waste heat recovery allow combined cycle resources to be modeled as complete configurations or as individual components. Users may assign resources to multiple environmental programs, which may include mass-based emission allowances, rate-based emission rate credits, or renewable energy credits.

EnCompass outage report

Position Report showing correlation between gas prices and production costs


EnCompass provides all of the necessary features to quantify the impacts of renewable and storage integration at the sub-hourly level.

EnCompass co-optimizes limited energy resources such as hydro, storage, and demand response with load shifting or “bounce back.” Users can model intermittent renewable resources such as wind and solar, which may be modeled with daily profile shapes down to the 1-minute level. Combined with the ramp rate restrictions on dispatchable resources, EnCompass provides all of the necessary features to quantify the impacts of renewable and storage integration at the sub-hourly level.

When planning maintenance for resources, users may enter historical or planned dates that repeat in the future, for example, every 12 or 18 months. Each potential outage may also have an allowable shift, which allows EnCompass to determine the optimal timing of planned outages within a region. Unplanned outages can then be randomly determined for each resource based on input forced outage rates and lengths. The structured scenarios within EnCompass make it easy to use the same outage schedule from a long-term parent scenario to multiple child scenarios.

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Utilize better reporting and tools to forecast expected future market conditions

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